Tough Tongue AI
AI teammate for high-stakes conversations
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Tough Tongue AI for Sales - Live AI teammate for every tough sales conversation

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Create *Live* AI teammates for every tough sales conversation. Each teammate shows up with human-like voice, avatar, and tools in minutes, can be deployed to phone, Google Meet, Zoom, or your application, and self-improves with every conversation. Use them to qualify leads, run autonomous product demos, coach new sales reps, and support your team live when the deal is on the line.

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Maker
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Hey Product Hunt! I’m Ajitesh, co-founder of Tough Tongue AI.

I built Tough Tongue AI to help people get better at tough conversations: interviews, negotiations, and especially sales. Some of these are repetitive but critical, and you can't keep up with all of them, so the agent steps in and runs them for you. Others are the ones that really matter, where it coaches you to show up sharper.

Being tough - but effective - is essential for sales calls. On one hand you have to really listen to your customer and understand their pain points and speak in their language, while on the other, you need to maximize their value to your business AND be mindful of building a long-term relationship.

To that end, today we're launching Tough Tongue AI for Sales: an AI sales team for SMBs that helps before, during, and after the sales conversation.

Before the call:

  • Reps can on phone, Zoom, Google Meet or within your CRM or sales hub

  • Teams can practice and learn to respond to objections, discovery questions, pricing pushback, and interruptions during demo flows

During the call:

  • AI agent can as part of pre-sales or reminder, , and book next steps

  • Brand new: “Truely” (our take on ) gives live help during meetings by pulling supporting facts from product docs, tickets, Linear, CRM, and other tools so you can stay in flow without losing context

After the call:

Even though Tough Tongue agents can answer inbound calls and call leads, our goal isn’t to replace the human closer. It is to make the sales conversations easier, faster, and more successful :)

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As a heavy dogfooder, here are a few tweaks to sales process that has worked for me:

  • Switched to reverse demo. This is especially useful for new and spread-out products like us. The goal is to deliver small wins for customers by solving their problem in 15-30 min and familiarize them with the platform. To prep for this I wrote a skill (), which can deep research prospects, generate the reverse demo prompt, and feed the context to Truely so I have live support during the call if I need :) Huge confidence booster.

  • Second, automated the product demo call on website where our AI agent does product demo 24*7 in prospect's preferred language on Google Meet. This has delivered 4X more meetings and engagement with leads when they need it - instantly, across time zones, even when I am asleep :)

  • Third, create roleplay from slack. I have skill for Tough Tongue AI scenario creation installed in my Codex and Claude that I can use from slack to do prospect research and create roleplay for meetings tomorrow. Even a one spin before the meeting gives me a lot of confidence.

Happy to chat more on this, and definitely recommend trying these out.
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I’ll be here all day answering questions. Thank you for checking us out!

For teams that want lower usage costs, we also support BYOK: bring your own Gemini and OpenAI keys and use Tough Tongue at 1 cent per minute (lowest in industry).

Oh and to celebrate our launch - I’m pleased to offer a 50% discount until 30th June 2026. Use code PH50 at checkout!

   huge congrats on the launch, so glad you explicitly stated the goal isn't to replace the human closer. sales tools that try to fully automate the entire pipeline always feel incredibly robotic, but using ai as a live coach during the call is the sweet spot.🙌

Maker

   This is exactly the line we are trying to stay honest about.

I also find fully automated sales pipelines a bit robotic, especially when the conversation needs trust, timing, and judgment. The way I think about it is: AI should take over the repetitive parts where speed matters, and support the human in moments where context matters.

So for some workflows, the agent can call, qualify, follow up, demo, or book the next step. But when the conversation is high-stakes, it should become a live teammate: pull the right fact, suggest the next question, remind you of the objection handling, and help you stay in flow.

That balance is what we’re trying to get right.

   

The coaching and roleplay side is a clear win. The AI-initiates-calls-to-real-prospects side is where I'd want to understand the trust dynamic better.

One question I keep coming back to though: for the live AI caller feature specifically, how does it handle the moment a prospect realises they're talking to an AI? Increasingly people can tell, and that realisation mid-call can damage the brand relationship more than a missed call would.

Curious whether you've measured pickup and engagement rates for AI-initiated calls vs human ones — and whether there's a transparency setting where the AI identifies itself upfront.

Maker

   his is a very fair question, and honestly one of the most important ones in this category.

I don’t think the goal should be to “trick” a prospect into thinking they are speaking with a human. That may work for a short period, but it is not a good long-term trust strategy for a brand.


The way I think about AI-initiated calls is that the use case matters a lot. If it is a warm lead, a reminder, a qualification call, a product demo they requested, or a follow-up where the purpose is clear, people are much more open to it. If it is cold outbound pretending to be human, the trust dynamic is very different and much riskier.


On transparency: yes, the opening and agent behavior can be configured, so the AI can identify itself upfront. In many workflows, I actually think that is the right default. The agent should be clear, useful, and easy to escalate from.


We also care a lot about measurement here: pickup, drop-off, engagement, booked next step, handoff rate, and negative reactions. My current view is that AI calling should be used where it increases responsiveness without hurting trust, and where the human handoff is obvious when the conversation becomes sensitive or high-value.

Would love to exchange notes on this offline too.

Hunter

Sales enablement usually feels pretty awkward: it's either generic training content, or call reviews after the moment has passed.

's approach for Tough Tongue earns its namesake: it’s closer to a quick-witted sparring partner for SMB sales teams. You get to role play before the call, get live help during the meeting, and a call audit once it's over.

Some else that's new: “Truely” (their in-call assistant modeled after ), can pull from context while the call's happening — not to deliver vague chatbottery, but to help demo, qualify, and secure the next meeting.

It's free to start, with 50% for 2 months with their Product Hunt launch deal!

If you’re doing founder-led sales or trying to get your team sharpened up on calls, have you considered an agentic tongue lashing? You might be surprised! 😜

Maker

 Chris. This means a lot, especially because you’ve seen the product and the story evolve up close.

Your insights have helped us how we talk about the product and showcase to world (including our landing page).

Really grateful for your help in this whole launch process. And yes, we’ll try to make every agentic tongue lashing useful, not traumatic 😄

Maker

Hello Everyone,

Co-Founder of Tough Tongue AI here.

Thanks you for all the love and support on our launch.

Since the previous launch, our engineering team has diligently minted and perfected many features and workflows. My favourite one is Truely which gives your sales calls the much needed sidekick with just in time suggestions.

Apart from this, the team has made significant improvements and hacks for reliability and latency and perceived latency of realtime sessions. We now support a large selection of models and voices with automatic failover too so that your calls do not drop abruptly.

Also, we support on-request integrations like Shopify, Salesforce etc to further provide conveniences like being in sync with data and analytics from 1000s of agent sessions. Talk to us for such use cases!

I am also looking to hear feature requests and suggestions in the comments. Your feedback has contributed immensely in shaping the product to what it is today.

Thanks,

Raj

Really like the direction you're taking by covering the entire sales lifecycle.

How does Tough Tongue AI measure whether an agent is actually improving over time? Do you track metrics like conversion rates, objection handling

Maker

 Yes, but we think about “improvement” at 3 levels:

  1. Business outcomes: response time, connect rate, qualified leads, demos completed, meetings booked, follow-up completion, and where available, downstream conversion. That's what most our customers care about post pilot.

  2. Conversation quality: did the agent ask the right discovery questions, handle objections correctly, follow pricing/qualification rules, know when to escalate, and keep the buyer moving to a clear next step.

  3. Learning loop: every call can flag missing knowledge, weak objection handling, confusing product docs, or new buyer patterns. The agent proposes updates, but the human approves what actually becomes part of the playbook.

Hope this helps!

Giving honest feedback is hard, especially when you don't want to damage a relationship. I like that Tough Tongue AI tackles a very human problem instead of just another productivity use case. I'm curious, what kind of conversations do people practice the most with it?

Maker

 I really like how you framed this. The human part is exactly why we started with tough conversations before narrowing into sales.

The most common practice areas right now are discovery calls, pricing pushback, objection handling, demo interruptions, qualification, and follow-ups. Outside sales, people also use it for interviews, feedback conversations, negotiation, and customer support scenarios.

For sales teams, the most interesting pattern is that practice does not stay separate from the real workflow: the same playbook can help the agent call leads, support the rep live, and audit what happened afterward.


Happy to connect offline too if you want to compare notes on the kinds of conversations you’re thinking about.

Congrats on the launch, Ajitesh. I really like the before / during / after framing here. sales conversations are rarely just about saying the right thing, they’re about right timing, emotional read and knowing when to push or slow down.

How you think about the line between AI acting autonomously in a sales conversation and AI staying in a coaching/support role for the human rep?

Maker

 you put this beautifully.

I think the autonomy line should be set by the business and by the risk of the conversation.

  • For repetitive frontline work like reminders, qualification, basic demos, follow-ups, and booking next steps, an AI agent can act directly if the rules are clear. Most users we interact with find this part less rewarding and boring.

  • For high-trust moments, complex objections, pricing judgment, or sensitive buyer context, the better role is coaching/support: bring the right context to the human, suggest what to ask, and help capture what happened.

Would be happy to discuss this offline too. I think this boundary is one of the most important design questions in AI sales.

Smart! Will surely give it a try!

Maker

 Thanks so much Ruvik! If you have a specific sales flow, demo, or lead follow-up workflow in mind, send it over and I’d be happy to help you set up the first agent.

All the best for the launch & team!

Maker

 Thanks so much Tanmay! We should connect some time to explore we can collaborate and work some project :)

When Truely pulls context from CRM and docs during a live call - how fast does it surface the info? Curious if there's any lag that might break the flow of the conversation.

Maker

great question. For Truely, speed is basically the product. If the context arrives after the moment has passed, it is not useful.

The way we think about it is: prepare as much context as possible before the call, retrieve only the most relevant pieces during the call, and surface short, glanceable help instead of long AI responses. The goal is not to make the rep pause and read a paragraph, but to give them the right fact, objection answer, customer context, or next-step suggestion while they stay in flow.

Latency can vary based on the data source and setup, but we’re designing around live conversation constraints. Happy to connect offline if you want to dig into the architecture or a specific CRM/docs workflow.

💎 Pixel perfection

Sales coaching is a strong use case for AI because the feedback loop is usually too slow. By the time a call is reviewed, the moment has passed.

The part I’d be most interested in is how the live assistant stays useful without distracting the rep. The best sales AI should surface the next sharp question, risk, or objection cue at the right time, not overwhelm the conversation with generic prompts.

Maker

 this is exactly the area where I’ve spent the most time researching. Almost every GTM enablement team I spoke with brought up the same risk: if the assistant is always “looking at the call,” it can easily become distracting

  • What I found interesting is that only a small set of reps, maybe 20%, feel confident enough to not want any help in the room. Most reps still miss things: pricing nuance, positioning, competitor context, a sharper discovery question, or the right next step. So the design challenge becomes: how do you support them without flooding them?

  • Our current POV is that the agent needs to be highly controllable. For example, if a pricing question comes up, it should surface 3 crisp bullets and nothing else. You can create your own agent with strict constraints, connect it to CRM or knowledge sources through MCP/custom functions, and decide exactly when it should surface something.

So I fully agree with your point. The two pieces we’re focusing on are user control and rich context, so the assistant is useful because it knows the situation, not because it is randomly generating prompts.

Would love to hear more of your thoughts on this. If you’re open to it, happy to connect offline:


This makes a lot of sense. The “3 crisp bullets and nothing else” idea is exactly the kind of restraint that would make a live sales assistant usable instead of distracting.

The controllability point feels important too. Different reps probably need different levels of help: newer reps may want more cues, while senior reps may only want pricing, competitor context, or risk flags. If Tough Tongue can let teams tune when the agent speaks, what sources it can use, and what it should never interrupt for, that becomes much more practical for real GTM teams.

Happy to connect offline. I’ll take a look at your calendar link.

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